Loss of shear stress induces leukocyte‐mediated cytokine release and blood–brain barrier failure in dynamic in vitro blood–brain barrier model
Bibliographic record
Abstract
Brain ischemia is associated with an acute release of pro-inflammatory cytokines, notably TNF-alpha and IL-6 and failure of the blood-brain barrier. Shear stress, hypoxia-hypoglycemia, and blood leukocytes play a significant role in blood-brain barrier failure during transient or permanent ischemia. However, these mechanisms have not been studied as independent variables for in vitro ischemia. The present study, using a dynamic in vitro blood-brain barrier model, showed that flow cessation/reperfusion under normoxia-normoglycemia or hypoxia-hypoglycemia without blood leukocytes in the luminal perfusate had a modest, transient effect on cytokine release and blood-brain barrier permeability. By contrast, exposure to normoxic-normoglycemic flow cessation/reperfusion with blood leukocytes in the luminal perfusate led to a significant increase in TNF-alpha and IL-6, accompanied by biphasic blood-brain barrier opening. Enhanced permeability was partially prevented with an anti-TNF-alpha antibody. In leukocyte-free cartridges, the same levels of IL-6 had no effect, while TNF-alpha caused a moderate increase in blood-brain barrier permeability, suggesting that blood leukocytes are the prerequisite for cytokine release and blood-brain barrier failure during reduction or cessation of flow. These cells induce release of TNF-alpha early after ischemia/reperfusion; TNF-alpha triggers release of IL-6, since blockade of TNF-alpha prevents IL-6 release, whereas blockade of IL-6 induces TNF-alpha release. Pre-treatment of blood leukocytes with the cyclooxygenase (COX) inhibitor, ibuprofen, inhibited cytokine release and completely preserved blood-brain barrier permeability during the reperfusion period. In conclusion, loss of flow (flow cessation/reperfusion) independent of hypoxia-hypoglycemia plays a significant role in blood-brain barrier failure by stimulating leukocyte-mediated inflammatory mechanisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".